Check the full description for links to all the resources and the protocol etc. This tutorial follows the Delhomme et al. Epigenesys protocol for RNA sequencing data preprocessing in order to finally perform a differential expression study. To demonstrate, we ...

Learn about sample requirements, library preparation and sequencing. Find out about our rigorous data analysis and biological interpretation of the results. See our recommendations for validating your NGS data and important next steps.

Nathan Salomonis – Video illustrating how easy it is to analyze transcriptome datasets in AltAnalyze. Here we analyze a published single-cell gene expression dataset, supplied as a supplemental table, according to known biological groups and using a de novo ...

Functional Analysis of Your RNAseq Data – Fiona McCarthy, University of Arizona The broad applicability and availability of RNASeq data has accelerated the generation of functional genomics data sets across a wide range of species. However, the end point of ...

Infection by West Nile Virus (WNV) is a worldwide public health concern, being the most common cause of epidemic viral encephalitis in USA, yet the viral pathogenesis is not well understood. Using QIAGEN Ingenuity Pathway Analysis’ features, we were ...

MIT 7.91J Foundations of Computational and Systems Biology, Spring 2014 View the complete course: http://ocw.mit.edu/7-91JS14 Instructor: David Gifford This lecture by Prof. David Gifford is about RNA-seq (RNA sequencing), a method of characterizing RNA molecules through next-generation sequencing. He begins with the ...

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What is RNA-Seq?

long RNAs are first converted into a library of cDNA fragments through either RNA fragmentation or DNA fragmentation. Sequencing adaptors (blue) are subsequently added to each cDNA fragment and a short sequence is obtained from each cDNA using high-throughput sequencing technology. The resulting sequence reads are aligned with the reference genome or transcriptome, and classified as three types: exonic reads, junction reads and poly(A) end-reads. These three types are used to generate a base-resolution expression profile for each gene. Nat Rev Genet 10(1):57-63 (2009)